MATH 1140
Computational Mathematics
(3,3,0) (E)
Prerequisite: MATH 1000 Supplementary Mathematics (Calculus
and Linear Algebra) or Grade D or above in AL
Pure Mathematics
This course aims to introduce Computer Science major students to
the basic concepts in modern computational mathematics and its
application. It provides various solid fundamental concepts and
knowledge for modelling, real life application and optimization.
Topics include advanced vector Algebra, number system, linear
systems, various numerical methods, power method, numerical
optimization and multivariable calculus. Practical applications
and programming techniques are both emphasized.
MATH 1205
Discrete Mathematics
(3,3,0) (E)
This course integrates the fundamental topics in discrete
mathematics and linear system. These topics, including
propositional logic, proof methods, set theory, combinatorics,
graph algorithms, Boolean algebra, and system of linear
equations, are essential for precise processing of information.
MATH 1550
Calculus and Linear Algebra
(3,3,0)
This course introduces topics in linear algebra, mathematical
analysis and differential equations. Applications to chemistry are
provided.
MATH 1590
Calculus and Linear Algebra for
(3,3,0) (E)
Chemistry
This course introduces topics in linear algebra, mathematical
analysis and differential equations. Applications to chemistry are
provided.
MATH 1006
Advanced Calculus I
(3,3,0)
Antirequisite: MATH 1005 Calculus
This course deals with the basic theory of analysis in real-valued
functions in single variable. It provides students with a good
foundation for more advanced courses in the mathematical
science major. Topics include real numbers, sequences, limit and
continuity, and differentiation.
MATH 2005
Probability and Statistics for
(3,3,0) (E)
Computer Science
Antirequisite: MATH 2006 Probability and Statistics for Science
and MATH 2206 Probability and Statistics
Prerequisite: MATH 1005 Calculus; student with credit for
MATH 2006 or MATH 2206 are not allowed to
take MATH 2005 for further credit
This course aims to provide an understanding of the basic
concepts in probability and statistical analysis, and focuses
on applied probability and statistics. Students will learn the
fundamental concepts of random variables, the basic concepts
and techniques of parameter estimation and hypothesis testing.
After taking this course, students will be able to apply the concepts
to real-life IT/engineering problems and use popular statistics
software, such as SPSS, SAS to perform analysis.
MATH 2006
Probability and Statistics for
(3,3,0) (E)
Science
Antirequisite: MATH 2005 Probability and Statistics for Science
and MATH 2206 Probability and Statistics
Prerequisite: MATH 1005 Calculus; students with credit for
MATH 2005 or MATH 2206 are not allowed to
take MATH 2006 for further credit
This course aims to provide an understanding of the basic
concepts in probability and statistical analysis, and focuses
on applied probability and statistics. Students will learn the
fundamental concepts of random variables, the basic concepts and
MATH 2110
Differential Equations
(3,3,0) (E)
Prerequisite: MATH 1111 Mathematical Analysis I, MATH
1112 Mathematical Analysis II and MATH 1120
Linear Algebra
This course aims to introduce students to the basic theory of
ordinary differential equations and the modelling of diverse
practical phenomena by ordinary differential equations by a
variety of examples. Students will learn both quantitative and
qualitative methods for solving these equations. Topics include
first and second order differential equations, linear systems of first
order differential equations, autonomous systems of differential
equations, existence and uniqueness theorem and Laplace
transform to initial value problem.
MATH 2130
Real Analysis
(3,3,0) (E)
Prerequisite: MATH 1111 Mathematical Analysis I
This course provides an introduction to measure theory, Lebesgue
integration, LP spaces, and Fourier analysis. Equipped with this
knowledge, students are prepared for further studies in numerical
analysis, functional analysis and advanced probability theory.
MATH 2140
Numerical Methods I
(3,3,0) (E)
Prerequisite:
Year II standing
This course provides students with the ideas underlying
commonly used numerical methods. It teaches students how to
choose an appropriate numerical method for a particular problem
and to interpret the resulting output. It also highlights important
considerations on convergence and stability for numerical
algorithm design.
MATH 2150
Mathematical Analysis III
(3,3,0) (E)
Prerequisite: MATH 1111-2 Mathematical Analysis I & II
(MATH 1120 Linear Algebra is not required but
recommended)
This course deals with vectors calculus. It provides basic concept
on several variables real-valued functions. Topics include
sequences in space, limit and continuity, differentiation, Riemann
integrals, multiple integrals, line integrals and surface integrals.
MATH 2160
Mathematical and Statistical
(3,1,2)
Software
Prerequisite: COMP 1170 Structured Programming
This course teaches students how to use some popular software
packages for solving problems in various areas of mathematics,
statistics and operations research. Examples of software packages
that may be covered are MATLAB, SAS, S-plus, LINDO, and
Latex. Students will learn both how to use these software
packages to efficiently to solve the related problems and how
to interpret the results. Such knowledge should be useful for
students' course work, projects and future careers.
MATH 2205
Multivariate Calculus
(3,3,1) (E)
Prerequisite: MATH 1005 Calculus, MATH 2207 Linear
Algebra or MATH 1205 Discrete Mathematics
(recommended)
This course deals with calculus and functions of several variables.
Students should know the basic concepts and technique of
univariate calculus. Some knowledge on linear algebra, such as
matrix notations and calculations, is preferred. Topics include
partial derivative, multiple integral, and their theories and
applications.
MATH 2206
Probability and Statistics
(3,3,1)
Antirequisite: MATH 2005 Probability and Statistics for Science
and MATH 2206 Probability and Statistics
This course deals with probability and statistical methods. The
emphasis is on what, how, when and why certain probability
model and statistical methods can and cannot be applied. Topics
449
Course Descriptions
MATH 1570
Advanced Calculus
(3,3,0) (E)
Prerequisite: Year I standing
This course gives students fundamental mathematical knowledge
in a wide variety of areas including vector algebra, vector
differentiation and integration, as well as an introduction to baisc
linear algebra.
techniques of parameter estimation and hypothesis testing. After
taking this course, students will be able to apply the concepts and
methods to solve different problems in Science and use popular
statistics packages, such as SPSS, SAS to perform analysis.